Representing Probabilistic Knowledge in Relational Databases

Abstract:
As knowledge bases are enlarged to support more complex classes of problems,
expert systems will demand efficient knowledge-management techniques--
techniques that are already available in database systems. In this paper, we
present the design of a database schema suitable for knowledge bases that
employ a decision-network representation. Using this schema, we describe the
process of translating existing knowledge bases into relational format.
Although exploratory in nature, our work indicates that the application of
database techniques offers numerous advantages over an ad-hoc scheme for
managing probabilistic knowledge bases.